title: Multivariate temporal symptomatic characterization of cardiac arrest.
abstract: We model the temporal symptomatic characteristics of 171 cardiac arrest patients in Intensive Care Units. The temporal and feature dependencies in the data are illustrated using a mixture of matrix normal distributions. We found that the cardiac arrest temporal signature is best summarized with six hours data prior to cardiac arrest events, and its statistical descriptions are significantly different from the measurements taken in the past two days. This matrix normal model can classify these patterns better than logistic regressions with lagged features.
authors.forename: Yubin
authors.initials: Y
authors.lastname: Park
authors.forename: Joyce C
authors.initials: JC
authors.lastname: Ho
authors.forename: Joydeep
authors.initials: J
authors.lastname: Ghosh
mesh_terms: D000328:Adult; D019540:Area Under Curve; D001795:Blood Pressure Determination; D006323:Heart Arrest / Q000175:diagnosis* / Q000503:physiopathology; D006801:Humans; D016015:Logistic Models; D015999:Multivariate Analysis; D012372:ROC Curve; D013997:Time Factors